moved utility functions from gpu_perf_test and gpu_test to ts module
This commit is contained in:
Vladislav Vinogradov
@@ -43,306 +43,7 @@
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#ifdef HAVE_CUDA
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namespace
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{
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bool keyPointsEquals(const cv::KeyPoint& p1, const cv::KeyPoint& p2)
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{
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const double maxPtDif = 1.0;
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const double maxSizeDif = 1.0;
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const double maxAngleDif = 2.0;
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const double maxResponseDif = 0.1;
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double dist = cv::norm(p1.pt - p2.pt);
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if (dist < maxPtDif &&
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fabs(p1.size - p2.size) < maxSizeDif &&
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abs(p1.angle - p2.angle) < maxAngleDif &&
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abs(p1.response - p2.response) < maxResponseDif &&
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p1.octave == p2.octave &&
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p1.class_id == p2.class_id)
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{
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return true;
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}
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return false;
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}
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struct KeyPointLess : std::binary_function<cv::KeyPoint, cv::KeyPoint, bool>
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{
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bool operator()(const cv::KeyPoint& kp1, const cv::KeyPoint& kp2) const
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{
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return kp1.pt.y < kp2.pt.y || (kp1.pt.y == kp2.pt.y && kp1.pt.x < kp2.pt.x);
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}
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};
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testing::AssertionResult assertKeyPointsEquals(const char* gold_expr, const char* actual_expr, std::vector<cv::KeyPoint>& gold, std::vector<cv::KeyPoint>& actual)
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{
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if (gold.size() != actual.size())
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{
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return testing::AssertionFailure() << "KeyPoints size mistmach\n"
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<< "\"" << gold_expr << "\" : " << gold.size() << "\n"
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<< "\"" << actual_expr << "\" : " << actual.size();
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}
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std::sort(actual.begin(), actual.end(), KeyPointLess());
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std::sort(gold.begin(), gold.end(), KeyPointLess());
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for (size_t i = 0; i < gold.size(); ++i)
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{
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const cv::KeyPoint& p1 = gold[i];
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const cv::KeyPoint& p2 = actual[i];
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if (!keyPointsEquals(p1, p2))
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{
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return testing::AssertionFailure() << "KeyPoints differ at " << i << "\n"
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<< "\"" << gold_expr << "\" vs \"" << actual_expr << "\" : \n"
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<< "pt : " << testing::PrintToString(p1.pt) << " vs " << testing::PrintToString(p2.pt) << "\n"
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<< "size : " << p1.size << " vs " << p2.size << "\n"
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<< "angle : " << p1.angle << " vs " << p2.angle << "\n"
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<< "response : " << p1.response << " vs " << p2.response << "\n"
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<< "octave : " << p1.octave << " vs " << p2.octave << "\n"
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<< "class_id : " << p1.class_id << " vs " << p2.class_id;
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}
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}
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return ::testing::AssertionSuccess();
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}
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#define ASSERT_KEYPOINTS_EQ(gold, actual) EXPECT_PRED_FORMAT2(assertKeyPointsEquals, gold, actual);
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int getMatchedPointsCount(std::vector<cv::KeyPoint>& gold, std::vector<cv::KeyPoint>& actual)
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{
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std::sort(actual.begin(), actual.end(), KeyPointLess());
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std::sort(gold.begin(), gold.end(), KeyPointLess());
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int validCount = 0;
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for (size_t i = 0; i < gold.size(); ++i)
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{
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const cv::KeyPoint& p1 = gold[i];
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const cv::KeyPoint& p2 = actual[i];
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if (keyPointsEquals(p1, p2))
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++validCount;
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}
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return validCount;
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}
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int getMatchedPointsCount(const std::vector<cv::KeyPoint>& keypoints1, const std::vector<cv::KeyPoint>& keypoints2, const std::vector<cv::DMatch>& matches)
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{
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int validCount = 0;
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for (size_t i = 0; i < matches.size(); ++i)
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{
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const cv::DMatch& m = matches[i];
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const cv::KeyPoint& p1 = keypoints1[m.queryIdx];
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const cv::KeyPoint& p2 = keypoints2[m.trainIdx];
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if (keyPointsEquals(p1, p2))
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++validCount;
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}
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return validCount;
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}
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}
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/////////////////////////////////////////////////////////////////////////////////////////////////
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// SURF
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namespace
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{
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IMPLEMENT_PARAM_CLASS(SURF_HessianThreshold, double)
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IMPLEMENT_PARAM_CLASS(SURF_Octaves, int)
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IMPLEMENT_PARAM_CLASS(SURF_OctaveLayers, int)
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IMPLEMENT_PARAM_CLASS(SURF_Extended, bool)
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IMPLEMENT_PARAM_CLASS(SURF_Upright, bool)
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}
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PARAM_TEST_CASE(SURF, cv::gpu::DeviceInfo, SURF_HessianThreshold, SURF_Octaves, SURF_OctaveLayers, SURF_Extended, SURF_Upright)
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{
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cv::gpu::DeviceInfo devInfo;
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double hessianThreshold;
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int nOctaves;
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int nOctaveLayers;
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bool extended;
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bool upright;
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virtual void SetUp()
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{
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devInfo = GET_PARAM(0);
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hessianThreshold = GET_PARAM(1);
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nOctaves = GET_PARAM(2);
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nOctaveLayers = GET_PARAM(3);
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extended = GET_PARAM(4);
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upright = GET_PARAM(5);
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cv::gpu::setDevice(devInfo.deviceID());
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}
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};
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GPU_TEST_P(SURF, Detector)
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{
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cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(image.empty());
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cv::gpu::SURF_GPU surf;
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surf.hessianThreshold = hessianThreshold;
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surf.nOctaves = nOctaves;
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surf.nOctaveLayers = nOctaveLayers;
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surf.extended = extended;
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surf.upright = upright;
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surf.keypointsRatio = 0.05f;
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if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
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{
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try
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{
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std::vector<cv::KeyPoint> keypoints;
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surf(loadMat(image), cv::gpu::GpuMat(), keypoints);
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}
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catch (const cv::Exception& e)
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{
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ASSERT_EQ(CV_StsNotImplemented, e.code);
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}
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}
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else
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{
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std::vector<cv::KeyPoint> keypoints;
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surf(loadMat(image), cv::gpu::GpuMat(), keypoints);
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cv::SURF surf_gold;
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surf_gold.hessianThreshold = hessianThreshold;
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surf_gold.nOctaves = nOctaves;
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surf_gold.nOctaveLayers = nOctaveLayers;
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surf_gold.extended = extended;
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surf_gold.upright = upright;
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std::vector<cv::KeyPoint> keypoints_gold;
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surf_gold(image, cv::noArray(), keypoints_gold);
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ASSERT_EQ(keypoints_gold.size(), keypoints.size());
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int matchedCount = getMatchedPointsCount(keypoints_gold, keypoints);
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double matchedRatio = static_cast<double>(matchedCount) / keypoints_gold.size();
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EXPECT_GT(matchedRatio, 0.95);
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}
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}
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GPU_TEST_P(SURF, Detector_Masked)
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{
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cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(image.empty());
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cv::Mat mask(image.size(), CV_8UC1, cv::Scalar::all(1));
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mask(cv::Range(0, image.rows / 2), cv::Range(0, image.cols / 2)).setTo(cv::Scalar::all(0));
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cv::gpu::SURF_GPU surf;
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surf.hessianThreshold = hessianThreshold;
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surf.nOctaves = nOctaves;
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surf.nOctaveLayers = nOctaveLayers;
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surf.extended = extended;
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surf.upright = upright;
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surf.keypointsRatio = 0.05f;
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if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
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{
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try
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{
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std::vector<cv::KeyPoint> keypoints;
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surf(loadMat(image), loadMat(mask), keypoints);
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}
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catch (const cv::Exception& e)
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{
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ASSERT_EQ(CV_StsNotImplemented, e.code);
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}
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}
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else
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{
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std::vector<cv::KeyPoint> keypoints;
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surf(loadMat(image), loadMat(mask), keypoints);
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cv::SURF surf_gold;
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surf_gold.hessianThreshold = hessianThreshold;
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surf_gold.nOctaves = nOctaves;
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surf_gold.nOctaveLayers = nOctaveLayers;
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surf_gold.extended = extended;
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surf_gold.upright = upright;
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std::vector<cv::KeyPoint> keypoints_gold;
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surf_gold(image, mask, keypoints_gold);
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ASSERT_EQ(keypoints_gold.size(), keypoints.size());
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int matchedCount = getMatchedPointsCount(keypoints_gold, keypoints);
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double matchedRatio = static_cast<double>(matchedCount) / keypoints_gold.size();
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EXPECT_GT(matchedRatio, 0.95);
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}
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}
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GPU_TEST_P(SURF, Descriptor)
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{
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cv::Mat image = readImage("features2d/aloe.png", cv::IMREAD_GRAYSCALE);
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ASSERT_FALSE(image.empty());
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cv::gpu::SURF_GPU surf;
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surf.hessianThreshold = hessianThreshold;
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surf.nOctaves = nOctaves;
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surf.nOctaveLayers = nOctaveLayers;
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surf.extended = extended;
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surf.upright = upright;
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surf.keypointsRatio = 0.05f;
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cv::SURF surf_gold;
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surf_gold.hessianThreshold = hessianThreshold;
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surf_gold.nOctaves = nOctaves;
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surf_gold.nOctaveLayers = nOctaveLayers;
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surf_gold.extended = extended;
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surf_gold.upright = upright;
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if (!supportFeature(devInfo, cv::gpu::GLOBAL_ATOMICS))
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{
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try
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{
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std::vector<cv::KeyPoint> keypoints;
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cv::gpu::GpuMat descriptors;
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surf(loadMat(image), cv::gpu::GpuMat(), keypoints, descriptors);
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}
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catch (const cv::Exception& e)
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{
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ASSERT_EQ(CV_StsNotImplemented, e.code);
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}
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}
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else
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{
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std::vector<cv::KeyPoint> keypoints;
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surf_gold(image, cv::noArray(), keypoints);
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cv::gpu::GpuMat descriptors;
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surf(loadMat(image), cv::gpu::GpuMat(), keypoints, descriptors, true);
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cv::Mat descriptors_gold;
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surf_gold(image, cv::noArray(), keypoints, descriptors_gold, true);
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cv::BFMatcher matcher(cv::NORM_L2);
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std::vector<cv::DMatch> matches;
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matcher.match(descriptors_gold, cv::Mat(descriptors), matches);
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int matchedCount = getMatchedPointsCount(keypoints, keypoints, matches);
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double matchedRatio = static_cast<double>(matchedCount) / keypoints.size();
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EXPECT_GT(matchedRatio, 0.6);
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}
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}
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INSTANTIATE_TEST_CASE_P(GPU_Features2D, SURF, testing::Combine(
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ALL_DEVICES,
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testing::Values(SURF_HessianThreshold(100.0), SURF_HessianThreshold(500.0), SURF_HessianThreshold(1000.0)),
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testing::Values(SURF_Octaves(3), SURF_Octaves(4)),
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testing::Values(SURF_OctaveLayers(2), SURF_OctaveLayers(3)),
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testing::Values(SURF_Extended(false), SURF_Extended(true)),
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testing::Values(SURF_Upright(false), SURF_Upright(true))));
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using namespace cvtest;
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/////////////////////////////////////////////////////////////////////////////////////////////////
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// FAST
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